high performance computing on graphics processing units: hgpu.org

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A Survey of Methods For Analyzing and Improving GPU Energy Efficiency

Sparsh Mittal, Jeffrey S. Vetter

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Tags: comparison, Computer science, cpu, CUDA, Energy-efficient computing, FPGA, Hardware Architecture, nVidia

April 18, 2014 by sparsh0mittal

Comparing CUDA, OpenCL and OpenGL Implementations of the Cardiac Monodomain Equations

Rafael Sachetto Oliveira, Bernardo Martins Rocha, Ronan Mendonça Amorim, Fernando Otaviano Campos, Wagner Meira Jr., Elson Magalhães Toledo, Rodrigo Weber dos Santos

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Tags: cardiac simulation, comparison, CUDA, OpenCL, OpenGL

August 2, 2013 by rbm84

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice

HeterPS: Distributed Deep Learning With Reinforcement Learning Based Scheduling in Heterogeneous Environments

BAT: A standardized benchmark suite for auto-tuners

BAT: A Benchmark suite for AutoTuners

The Darmstadt Automotive Parallel HeterogeNEous (DAPHNE) Benchmark-Suite

Programming Heterogeneous Systems with General and Domain-Specific Frameworks

General purpose lattice QCD code set Bridge++ 2.0 for high performance computing

MQBench: Towards Reproducible and Deployable Model Quantization Benchmark

Performance Evaluation of Python ParallelProgramming Models: Charm4Py and mpi4py

iGUARD: In-GPU Advanced Race Detection

TaPaSCo: The Task Parallel System Composer

Optimizing a Hardware Network Stack to Realize an In-Network ML Inference Application

Tapenade Automatic Differentiation Engine

Source-to-Source Automatic Differentiation of OpenMP Parallel Loops

Colossal-AI: an integrated large-scale model training system with efficient parallelization techniques

Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel Training

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